Abstract

The main ideas of the development of the software implementation of an algorithm for the fast automatic classification of seismic signals based on diagnostic patterns are described. The process of adaptation and integration of this implementation into the distributed computations system Apache Spark is described in detail. A software solution for the preliminary processing of the signals and optimization of the mathematical model for parallel computations using broadcast variables is presented. Performance tests for the classification algorithm on a set of day-long signals are carried out. The execution time of the algorithm in the context of massively parallel computations was reduced tenfold compared with the sequential execution.

中文翻译：

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Apache Spark框架中使用分布式计算对地震事件进行分类的快速算法

摘要

描述了基于诊断模式的地震信号快速自动分类算法的软件实现开发的主要思想。详细介绍了此实现的适应性和集成到分布式计算系统Apache Spark中的过程。提出了一种软件解决方案，用于信号的初步处理和使用广播变量进行并行计算的数学模型的优化。对分类算法进行了一系列为期一天的信号的性能测试。与顺序执行相比，在大规模并行计算环境中算法的执行时间减少了十倍。